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Nuclear power is a stable and reliable energy source that can improve energy structure while reducing carbon emissions, which is of great significance for environmental protection and combating climate change. As a unique industry, it is facing rare development opportunities in China and has broad market prospects. However, the characteristics of technical difficulty, loose organizational structure and uneven regional distribution limit the expansion of the nuclear power industry. This paper aims to a better understanding of the accumulation process for innovation capability from the perspective of network evolution and provides policy guidance for the market development of the nuclear power industry (NPI).

Methodologically, social network analysis is used to explore the co-evolution of multidimensional collaboration networks. First, the development and policy evolution of the NPI is introduced to divide the evolution periods. Then, the authors identify and analyze the core organizations, technologies and regions that promote nuclear power patent collaboration. Furthermore, three levels of collaboration networks based on organizations, technologies and regions are constructed to analyze the coevolution of patent networks in China’s NPI.

The results show that nuclear power enterprises always play the foremost role in the organizational collaboration network (OCN), and the dominance of foreign enterprises is replaced by Chinese state-owned enterprises in the third period. The technology hotspot has shifted from nuclear power plant construction to the control system. The regional collaboration network was initially formed in the coastal areas and gradually moved inland, with Guangdong and Beijing becoming the two cores of the network. The scale of three collaboration networks is still expanding but the speed has slowed down.

In response to the pain points of the NPI, this research focuses on multidimensional collaborative innovation, investigates the dynamic evolution process of collaborative innovation networks in China’s NPI and links policy evolution with network evolution creatively. The ultimate result not only helps nuclear power enterprises integrate innovative resources in complex environments but also promotes industrial upgrading and market development.

The purpose of this study is to address the low localization accuracy and frequent tracking failures of traditional visual SLAM methods in low-light and weak-texture situations, and we propose a mobile robot visual-inertial localization method based on the improved point-line features VINS-mono algorithm.

First, the line feature information is introduced into VINS-mono. Subsequently, the EDlines line feature extraction algorithm is optimized with a short line merging strategy and a dynamic length suppression strategy to reduce redundant short lines and fragmented segments. In the back-end sliding window optimization, line feature reprojection errors are incorporated, and Huber kernel functions are added to the inertial measurement unit residuals, point-line feature residuals and loop closure constraints to reduce the impact of outliers on the optimization results.

Comparison and verification experiments are carried out on the EuRoC MAV Data set and real weakly textured environment. In the real low-light and weak-texture scenarios, the improved mobile robot localization system achieves over 40% higher accuracy compared to VINS-mono.

The main contribution of this study is to propose a new visual-inertial SLAM method combining point-line features, which can achieve good localization effect in low-light and weak-texture scenes, with higher accuracy and robustness.

Radical innovation involves significant technological advances that have a critical impact on both firm growth and society development. Therefore, there is a growing need to understand how to achieve radical innovation. While previous studies have examined the direct effect of digitization on firm innovation, there is still limited knowledge of how digitization affects radical innovation. This paper aims to contribute to further exploring the underlying mechanism of how digitization affects radical innovation by incorporating the serial mediation effect of absorptive capacity.

This paper collected data from Chinese-listed manufacturing firms from 2015 to 2021 and analyzed the data using bootstrap analysis.

The research results show that digitization has a positive impact on radical innovation. Furthermore, digitization can influence radical innovation through potential absorptive capacity and realized absorptive capacity, and the mediation effect of potential absorptive capacity and realized absorptive capacity can occur sequentially. These research results are validated by a range of robustness tests.

This paper contributes to the literature on digitization and radical innovation by validating a model that links digitization through absorptive capacity to radical innovation. This model helps to explain the relationship between digitization and radical innovation, which has previously been a topic of debate. This paper also contributes to the absorptive capacity literature by unpacking the asymmetric roles of the potential absorptive capacity and the realized absorptive capacity. This paper also provides valuable implications for practices.

Although the literature has highlighted that a firm’s board is critical for firm innovation, the impact of board characteristics on firm innovation has always been examined separately, leading to inconclusive research results. Based on the complexity theory, this paper incorporates four board characteristics, including board size, board ownership, board independence and CEO duality, to examine the impact of the combinations of different board characteristics on firm innovation through qualitative comparative analysis.

Using the panel data of listed manufacturing firms in China from 2007 to 2022, this paper conducted the fuzzy set qualitative comparative analysis to test the proposed hypotheses.

The research results show that no single board characteristic can explain firm innovation, as board size, board ownership, board independence and CEO duality can lead to either positive or negative firm innovation. Moreover, firm innovation depends on a complex combination of board characteristics.

This paper makes the following contributions: Firstly, this paper advances the firm innovation literature by extending the role of board characteristics on firm innovation, thereby offering a new way to model firm innovation in terms of board characteristics. Secondly, this paper provides a more comprehensive account of the role of a firm’s board by integrating agency theory and resource dependence theory. Thirdly, this paper also identifies a promising avenue for further research in the field of corporate governance: the investigation of other contingency contexts in which the effect of board characteristics may be observed, with the aim of further increasing the understanding of board functioning.

With the rapid advancement of artificial intelligence (AI) technology permeating various sectors, corporate management has increasingly directed their focus toward AI-driven innovation. Particularly, in response to escalating environmental standards, chief executive officers (CEOs) of manufacturing companies are turning to AI as a strategic tool to address challenges in green innovation. This paper aims to reveal the complex relationship between CEO AI orientation and green innovation through the attention-based view. Furthermore, it seeks to explore strategies to enhance corporate green innovation leveraging CEO AI orientation.

The paper uses computer-assisted text analysis to extract data from annual reports of listed Chinese manufacturing companies and assesses them using negative binomial regression.

The empirical findings indicate the inverted U-shaped relationship between CEO orientation and green innovation. Initial green innovation performance increases with CEO AI orientation, reaching a peak before declining. Moreover, as CEO AI orientation increases, companies with higher levels of human resource slack are likely to reach the peak of green innovation earlier.

Firstly, this paper introduces CEO AI orientation as a novel factor within the framework of the attention-based view for understanding green innovation. Secondly, the study investigates both the benefit effect and the cost effect (resource constraints) of CEO AI orientation on green innovation, examining the inverted U-shaped relationship between CEO orientation and green innovation. Thirdly, this paper explores the moderating effect of human resource slack on the relationship between CEO AI orientation and green innovation, setting the boundaries of CEO AI orientation’s impact on green innovation.

This study empirically evaluates the effect of China’s 2016 Green Financial System (GFS) framework on corporate green development, focusing on the role of green investment in achieving sustainability.

This study uses a quasinatural experiment design to combine difference-in-difference and propensity score matching methods for analysis. It examines 799 polluting and 1,130 nonpolluting firms from 2013 to 2020, enabling a comprehensive assessment of the GFS framework’s influence.

This study affirms a statistically significant positive influence of the GFS framework on escalating green investment levels in polluting firms. Robust sensitivity analyses, encompassing parallel trend assessment, entropy balancing test, and alternative proxies, corroborate these findings. A mediation analysis identifies the implementation of an environmental management system as the potential underlying mechanism. A cross-sectional analysis identifies high financial slack, high profitability, mandatory CSR regulations, and marketization level as the influencing factors.

The study’s findings have critical implications for policymakers, regulators, and companies. Demonstrating the effectiveness of the GFS framework in driving green investment underscores the importance of aligning financial systems with sustainability goals.

This study contributes novel empirical evidence on the positive effect of China’s GFS framework on corporate green development. The quasinatural experiment design, coupled with comprehensive sensitivity analyses, strengthens the robustness of the findings.

This paper aims to explore the effect of different government subsidy decisions and the differences between the consequences of these decisions when supply chain members engage in cooperative green innovation through cost-sharing arrangements.

This paper investigates the optimal decisions for green supply chains under two types of subsidies, including subsidies for green innovation research and development (R&D) costs and subsidies for consumers, by integrating game theory with numerical simulation.

The optimal R&D cost-sharing ratio is found to be 2/3 for manufacturers and 1/3 for retailers. Under any subsidy policy, the supply chain can achieve maximum total profit. When the supply chain adopts the optimal R&D cost-sharing ratio, subsidies for green innovation R&D costs prove to be the most effective in increasing the supply chain’s profit. However, from the perspective of total social welfare, the analysis reveals that government subsidies to consumers are more beneficial for promoting overall social welfare.

Previous studies on green supply chain decisions have primarily focused on either government subsidies or corporate cost sharing in isolation. In contrast, this study combines both government subsidies and cost sharing within a unified framework for a more comprehensive analysis. Additionally, this paper examines the impact of government subsidies on supply chain cost-sharing decisions and their effect on overall social welfare while considering the presence of cost sharing and using the combination of theoretical modeling and simulation analysis.

The profound impact of the COVID-19 pandemic on the film industry has underscored the growing significance of online movies. However, there is limited research available on the factors that influence the viewership of online films. Therefore, this study aims to use the signaling theory to investigate how signals of varying qualities affect online movie viewership, considering both signal transmission costs and prices.

This study uses a sample of 1,071 online movies released on the iQiyi from July 2020 to July 2022. It uses OLS regression and instrumental variable method to examine the impact of various quality indicators on the viewership of online movies, as well as the moderating effect of price.

After conducting a thorough analysis of this study, it can be deduced that the varying impacts on online movie viewership are attributed to disparities in signal transmission costs. Specifically, star influence and rating exhibit a positive effect on the viewership of online movies, whereas the number of raters has a detrimental impact. Furthermore, there exists an “inverted U-shaped” relationship between the number of reviews and online movie viewership. Additionally, within the consumer decision-making process, both price-cost and price-quality relationships coexist. This is evident as prices negatively affect online movie viewership but positively moderate the relationship between rating, number of reviews and online movie viewership.

The research findings of this study offer valuable insights for online film producers to effectively leverage quality signals and pricing, thereby capturing market attention and enhancing film profitability.

This study offers a first conceptualisation of sustainable reverse innovation by discussing the contribution of innovation from the Global South towards sustainable development. In so doing, this study aims to recognise an active role played by developing countries in creating viable and innovative solutions that can contribute to the achievement of sustainable development for all.

This study presents five innovation vignettes and discusses them through an antecedents–enablers–consequences scheme for exploring the concept of sustainable reverse innovation. While discussing the model components, this study develops propositions to drive future research directions.

This study contributes to both development studies and innovation studies by recognising and highlighting the role played by businesses in addressing global challenges through sustainable innovation sourced from or inspired by developing countries.

To the best of the authors’ knowledge, this is the first study that offers a conceptualisation of sustainable reverse innovation that goes beyond the low-cost and frugality connotation that has characterised the debate surrounding innovation from emerging economies.

This study aims to examine the dynamic effect of FinTech on financial stability, with the moderating role of green finance (GF), its dimensions and mechanisms in the context of the spillover effects of the COVID-19 shock. This study used balanced panel data from 148 countries, including 76 developed and 72 emerging nations, from 2005 to 2022.

The research utilized the dynamic two-step system (GMM), and robustness was performed with the bootstrapped panel quantile regression.

The findings reveal that FinTech significantly affects financial stability across the entire sample. The overall composite of GF boosts financial stability by improving financial soundness. The GF dimensions, such as environmental, resource and financial, positively influence FS, while the GF economic dimension hurts FS. The moderating role and all interaction terms of GF dimensions with FinTech contribute positively and significantly to FS. While the interaction term GF resources with FinTech negatively impacts FS, indicating that countries should utilize resources more efficiently. Additionally, the COVID-19 spillover effect negatively influences FS across all samples. In advanced countries, FinTech and green finance positively affect FS. In emerging countries, green finance (except for the resource dimension) and FinTech interactions enhance financial stability, (except for the environmental dimension), leading to environmental hazards from their highly intensive industrial carbon policies.

The findings suggest that policymakers should prioritize promoting the adoption of initiatives related to FinTech and green finance by integrating sustainable transition finance policy frameworks to maintain stability and foster low-carbon economies for a sustainable future.

Improved financial stability has more significant social effects, such as better investment instruments, confidence and economic growth. Policymakers can leverage these findings to establish resilient financial ecosystems, fostering sustainable economic development and decreasing the risk of financial crises.

This study offers novel insights into how FinTech and multi-dimensional green finance effect financial stability in advanced and emerging nations. It provides unique insights into context-specific dynamics and enhances the literature on financial stability.